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New Zealand's Towns and Rural Centres 1976-2013

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New Zealand's Towns and Rural Centres 1976-2013 NIDEA WORKING NIDEA PAPERS National Institute of Demographic No 7 Nov 2016 and Economic Analysis New Zealand’s towns and rural centres 1976-2013 – experimental components of growth Natalie Jackson, Lars Brabyn and Dave Maré NIDEA Working Papers are intended as a forum for the publication of selected papers on research produced within the Institute, for discussion and comment among the research community and policy analysts prior to more formal refereeing and publication. The National Institute of Demographic and Economic Analysis (NIDEA) links together a virtual and evolving community of national and international researchers whose research focus is the interaction of demographic, social and economic processes. Initially founded through collaboration between the University of Waikato’s Population Studies Centre, Waikato Management School, and Wellington- based Motu Economic and Public Policy Research Trust, the Institute’s primary goal is to help inform choices and responses to the demographic, social and economic interactions that are shaping New Zealand’s future. Reflecting this objective, NIDEA’s research programme comprises five interconnected themes, and is supported and sustained by a strong capacity-building programme. Te Rūnanga Tātari Tatauranga | National Institute of Demographic and Economic Analysis Te Whare Wānanga o Waikato | The University of Waikato Private Bag 3105 | Hamilton 3240 | Waikato, New Zealand Email: [email protected] | visit us at: www.waikato.ac.nz/nidea/ ISSN 2230-441X (Print) ISSN 2230-4428 (Online) 2 | Page New Zealand’s towns and rural centres 1976-2013 – experimental components of growth1,2 Natalie Jackson, Lars Brabyn and Dave Maré Disclaimer The views expressed in this report are those of the authors and do not reflect any official position on the part of NIDEA or the University of Waikato. New Zealand’s towns and rural centres 1976-2013 – experimental components of growth1,2 1 Work on this paper was supported by a New Zealand Royal Society Marsden-Funded programme of research: Tai Timu Tangata: Taihoa e? (The subnational mechanisms of the ending of population growth: Towards a theory of depopulation) [Contract MAU1308]. 2 Description: The tables for towns and rural centres were created by Dave Maré (Motu Research) under microdata access agreement with Statistics New Zealand, MAA2003/18. [email protected]. The tables contain counts of the 1976, 1981, 1986, 1991, 1996, 2001, 2006 and 2013 usual resident population by age and sex, grouped by 2013 geographic area boundaries (Territorial Authority and Urban Area). The Urban Area classification has been extended to identify rural centres (ua13=501) separately (using 2013 Area Unit codes). The allocation to 2013 geographic areas is based on a user-derived correspondence. Just to reiterate the disclaimer, the counts are not official statistics but should be thought of estimates intended for use in research. Disclaimer: Access to the data used in this study was provided by Statistics New Zealand under conditions designed to give effect to the security and confidentiality provisions of the Statistics Act 1975. The results presented in these tables are the work of the author, not Statistics New Zealand 3 | Page Abstract In this paper we report on the approximate size, rate of change and contribution of migration and natural increase for 276 New Zealand towns and rural centres for the period 1976-2013. We also consider, by way of the Pearson correlation coefficient (‘r), a limited set of explanatory variables. We undertook this exercise as part of a broader analysis seeking to understand why some towns and centres grow and others don’t, following the formative work on urban populations by Grimes and Tarrant (2013). We also wanted to examine the extent to which New Zealand’s towns and rural centres may be following their international counterparts in declining from what Burcher and Mai (2005) propose is a ‘new’ form of population decline (where net migration loss is accompanied by natural decrease). However because the components of change (migration, births and deaths) are not available for most of these jurisdictions we had to first extract them via statistical means. Overall, we find a generally clustered pattern of growth and decline that fits well with Grimes and Tarrant’s results for their 60 main urban areas. We find that both growth from the combined effect of net migration gain and natural increase, and from natural increase offsetting net migration loss, is slowly giving way to decline from natural increase being unable to conceal net migration loss, more so for rural centres than towns. We also find the new form of population decline to be present, but as yet affecting very small numbers of towns and rural centres. At the same time, towns are more likely than rural centres to have proportions aged 65+ years in excess of 20 per cent. As a result they are experiencing a faster shift to natural decrease than rural centres. 4 | Page In this paper we report on the approximate size, rate of change and contribution of migration and natural increase (births minus deaths) for 276 New Zealand towns and rural centres for the period 1976-2013. We also consider, by way of the Pearson correlation coefficient (‘r), a limited set of explanatory variables following Johnson, Field and Poston (2015) in their comparison of the ‘counties’ of the United States (US) and Europe. We undertook this exercise as part of a broader analysis seeking to understand why some towns and centres grow and others don’t (Brabyn and Jackson forthcoming)3, following the formative work on urban populations by Grimes and Tarrant (2013). We also wanted to examine the extent to which New Zealand’s towns and rural centres may be following their international counterparts and declining from a new form of decline (where net migration loss is accompanied by natural decrease4) rather than the ‘old’ form (where natural increase was insufficient to offset net migration loss), as proposed by Burcher and Mai (2005, cited in Matanle and Rausch 2011: 19-20, 46-47). However because the components of change (migration, births and deaths) are not available for most of these jurisdictions, we had to first extract them via statistical means. In order to accommodate boundary changes, births by age of mother and population by age and sex also had to be aggregated to 2013 geographic area boundaries. The data sources and methodology are outlined below, followed by an overview of the results. Eight appendices contain detailed data generated by the analysis. Data Sources and Methodology: Ordinarily New Zealand’s census of population and dwellings is carried out in March at five year intervals (1976, 1981 etc.). However, with Statistics New Zealand’s head office located in Christchurch, the 2011 Christchurch earthquakes caused the 2011 census to be delayed to March 2013, resulting in a disruption to the time series and a seven year gap between 2006 and 2013. Where relevant, results are annualised. Population data: Mesh-block level counts of the usually resident population by 5-year age group (to 80+ years) and sex for all census years 1976-2013 were aggregated to the 2013 geographic area boundaries at urban area (UA) level (Database 1). The allocation to 2013 geographic areas was based on a ‘user-derived correspondence’. The counts are not official statistics but should be thought of 3 Both papers are supported by a Royal Society Marsden Fund grant (Contract MAU1308 - The subnational mechanisms of the ending of population growth. Towards a theory of depopulation). 4 Natural decrease is where deaths exceed births. 5 | Page experimental estimates intended for use in research.5 This exercise resulted in data for 143 urban areas and 133 rural centres. Birth and survivorship rates for all years for which these data were required are not available at urban area or rural centre level, and were instead constructed using indirect standardisation. In order to construct birth rates we purchased a customised dataset from Statistics New Zealand (2016) covering births by 5-year age group of mother for the period 1997-2013 (June years) at territorial authority area (TA) level and 2013 geographic boundaries. Survivorship (Lx) rates by age and sex for each TA were accessed for the years 2005-07 and 2012-14 (Statistics New Zealand 2015a). Calculating missing birth rates via indirect standardisation was done in two main steps. First, age- specific fertility rates were constructed for each of New Zealand’s 67 TAs for the June years 1996-97, 2001-02, and 2006-2013, using number of births by age of mother as sourced above, and female estimated resident population counts for corresponding 5-year age groups 15-49 years sourced from Statistics New Zealand (2015b). The age-specific fertility rates for 1996 and 2001 were then summed and averaged (for each age group and each TA), and their ratio to the equivalent rates for total New Zealand constructed (drawing on Statistics New Zealand 2015c). These relative age-specific fertility ratios for each TA were then held constant and multiplied by the equivalent rates for total New Zealand for the missing years, 1976, 1981, 1986, and 1991. That is, the national values were retrospectively inflated or deflated by the relevant ratio, for each of the four observations 1976- 1991, to generate approximate TA level age-specific rates for those years. The second step involved constructing age-specific fertility rates for each town and rural centre, by applying the age-specific rates for the TA in which each is located to the number of women in each 5-year age group 15-49 years, in each town and rural centre (from Database 1). The resulting birth rates and numbers at TA level differ slightly from those published by Statistics New Zealand (2015d) because they are constructed experimentally using both the ‘estimated resident population count’ (ERP) which includes adjustments for births, deaths and migration occurring between March and the ERP date (typically June or December), and the ‘usually resident population count’ (URP) at each five-yearly census (which is taken in March).
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